6. Retrieving Documents without Keys Using Views | Learning Couchbase

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Table Of Contents

Learning Couchbase

By : Henry Potsangbam

Learning Couchbase

By: Henry Potsangbam

Overview of this book

This book achieves its goal by taking up an end-to-end development structure, right from understanding NOSQL document design to implementing full fledged eCommerce application design using Couchbase as a backend. Starting with the architecture of Couchbase to get you up and running, this book quickly takes you through designing a NoSQL document and implementing highly scalable applications using Java API. You will then be introduced to document design and get to know the various ways to administer Couchbase. Followed by this, learn to store documents using bucket. Moving on, you will then learn to store, retrieve and delete documents using smart client base on Java API. You will then retrieve documents using SQL like syntax call N1QL. Next, you will learn how to write map reduce base views. Finally, you will configure XDCR for disaster recovery and implement an eCommerce application using Couchbase.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Introduction to Couchbase

1. Introduction to Couchbase

What is NoSQL and why do we need it?

The architecture of Couchbase

Concepts of Couchbase

Summary

2. The Couchbase Administration Interface

2. The Couchbase Administration Interface

The need for the Couchbase administrative interface

The web admin UI

Buckets and servers

Views

XDCR

Log

Settings

Couchbase administrative REST API

The command line interface

Summary

3. Storing Documents in Couchbase Using Buckets

3. Storing Documents in Couchbase Using Buckets

Buckets

Understanding documents

vBuckets

Understanding some internals of Couchbase

Summary

4. Designing a Document for Couchbase

4. Designing a Document for Couchbase

Understanding JSON and non JSON data

Document versus RDBMS

Document modeling

Document relationships

Using the document editor

Summary

5. Introducing Client SDK

5. Introducing Client SDK

A Couchbase SDK overview

Understanding write operation in the Couchbase cluster

Understanding the Couchbase API

Understanding Java SDK

Understanding locking

Understanding counters

async operations

Connection management

Summary

6. Retrieving Documents without Keys Using Views

6. Retrieving Documents without Keys Using Views

An overview of MapReduce

Views

Indexes

Understanding stale parameters

Built-in reduce functions

Custom reduce functions

Filtering and transforming data

Mapping with SQL to MapReduce

Understanding geospatial views

View writing guidance

Summary

7. Understanding SQL-Like Queries – N1QL

7. Understanding SQL-Like Queries – N1QL

The N1QL overview

Operation types

Understanding N1QL syntax

Indexing properties

Using the N1QL API

Summary

8. Full Text Search Using ElasticSearch

8. Full Text Search Using ElasticSearch

Understanding content-driven applications

Full text search overview

Configuration and query

Using the ES query API

An API to connect to ES

Summary

9. Data Replication and Compaction

9. Data Replication and Compaction

Understanding the XDCR architecture

Configuration and monitoring

Monitoring ongoing replications

The detailed replication progress

XDCR use cases

XDCR topologies

XDCR impact

Compaction

Summary

10. Administration, Tuning, and Monitoring

10. Administration, Tuning, and Monitoring

Overview

Backup and restoration

cbbackup

Rebalancing

Adding and removing a node from the cluster

Performing a bulk set

Monitoring

Best practices

Summary

11. Case Study – An E-Commerce Application

11. Case Study – An E-Commerce Application

Overview

The conceptual model

Summary

Index

Index

Filtering and transforming data

We have written views in the form of map and reduce functions. A view creates indexes and stores them on disk for all documents with the output of map function, along with reduce function's output. Couchbase provides a filtering mechanism for documents generated by views. We can also perform some transformation on data using; the group level, which is discussed subsequently.

Using keys

We can specify key values to filter documents while querying views, like this:

key="2008"

We can also specify a key explicitly to get only that particular key's details. Here, we will get only the view record that pertains to the 2008 key, as follows:

The following screenshot shows the interface to key in the, key to filter indexes:

Key interface

When you execute the view with the preceding key filter, you will only see records that pertain to the particular key, as shown here:

View result

keys=["2007","2008"]

We can explicitly specify a list of keys to get only those particular keys...

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